Download Standard Normal Curve (%) Graphing Calculator Instructions

Graphing the Standard Normal Curve
The Normal Probability Distribution menu for the TI-83+/84+ is
found under DISTR (2nd VARS).
NOTE: The default is µ = 0 and σ = 1
The Normal Distribution functions:
#1: normalpdf pdf = Probability Density Function – used to GRAPH a normal curve with the
given mean and standard deviation.
Syntax: normalpdf (x, mean, standard deviation)
#2: normalcdf cdf = Cumulative Distribution Function – used to CALCULATE the percentage
of the area given.
Syntax: normalcdf (lower bound, upper bound, mean, standard deviation)
#3: invNorm( inv = Inverse Normal Probability Distribution Function – this gives the x-value
when given the percentile.
Syntax: invNorm (probability, mean, standard deviation)
To find ShadeNorm( go to DISTR and right arrow to DRAW. Choose #1:ShadeNorm(.
#1:ShadeNorm( = Shading area – this allows us to calculate percentiles while looking at the
area of the normal curve that the data creates.
Syntax: ShadeNorm (lower bound, upperbound, mean, standard deviation)
Example 1:
Graph and investigate the normal distribution curve where the mean is 0 and
the standard deviation is 1.
Go to the Y = menu.
Adjust the WINDOW.
GRAPH.
You will have to set your own
window. Guideline is:
Xmin = mean - 3 SD
Xmax = mean + 3 SD
Xscl = SD
Ymin = 0
Ymax = 1/(2 SD)
Yscl = 0
Now, the area under the curve between particular values
represents the probabilities of events occurring within that
specific range. This area can be seen using the command
ShadeNorm(.
By entering parameters -1,1 you will see the area, indicating
approximately 68% probability of a score falling within 1
standard deviation from the mean in a normally distributed set of values.
Example 2:
Given a normal distribution of values for which µ is 70 and σ is 4.5, find:
a) the probability that a value is between 65 and 80, inclusive.
b) the probability that a value is greater than or equal to 75.
c) the probability that a value is less than 62.
d) the 90th percentile for this distribution.
1a:
1b:
1c:
1d: